ReviewBiology of sport2023
A review of machine learning applications in soccer with an emphasis on injury risk.
Review in Biology of sport, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 3 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
24 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Machine learning models for injury risk prediction in football players: A systematic review of predictors, performance, practical applications, and limitations.The Journal of international medical research · 2026Pooled it
- The Role of Machine Learning in Talent Identification for Team Sports: A Systematic Review.Journal of sports science & medicine · 2026Pooled it
- Machine Learning Applications in Non-Contact Lower Limb Sports Injury Prediction: A Systematic Review.Journal of sports science & medicine · 2026Pooled it
- Artificial Intelligence and Psychophysiological Monitoring for Integrated Performance Modeling in Elite Soccer: A Scoping Review of Applications, Evidence Gaps, and Translational Challenges.Sports (Basel, Switzerland) · 2026Review
- Application of Artificial Intelligence for Predicting Sports Injuries and Customizing Personalized Prevention Strategies: A Scoping Review.Bioengineering (Basel, Switzerland) · 2026Review
- Can We Predict Adductor Strain? A Predictive Analysis of a Major League Soccer (MLS) Cohort Spanning from 2019 to 2022.Journal of functional morphology and kinesiology · 2026Article
- Position prediction from performance and anthropometric indicators in young footballers: a machine learning approach.Scientific reports · 2026Article
- Generative artificial intelligence and large language models in sports medicine: a scoping review of applications, accuracy, and ethical implications.Frontiers in public health · 2026Article
- A Machine Learning Model for Post-Concussion Musculoskeletal Injury Risk in Collegiate Athletes.Sports medicine (Auckland, N.Z.) · 2025Article
- Review Articles on Soccer Performance Analysis: A Bibliometric Analysis of Current Trends and Emerging Themes.Sports (Basel, Switzerland) · 2025Review
- A Machine Learning Model for Post-Concussion Musculoskeletal Injury Risk in Collegiate Athletes.medRxiv : the preprint server for health sciences · 2025Article
- Reimagining athlete monitoring for true indicative injury prevention.BMJ open sport & exercise medicine · 2025Article
- Goal and shot prediction in ball possessions in FIFA Women's World Cup 2023: a machine learning approach.Frontiers in psychology · 2025Article
- Diagnostic Applications of AI in Sports: A Comprehensive Review of Injury Risk Prediction Methods.Diagnostics (Basel, Switzerland) · 2024Review
- Enhancing Sports Injury Risk Assessment in Soccer Through Machine Learning and Training Load Analysis.Journal of sports science & medicine · 2024Article
- Analyzing ECG signals in professional football players using machine learning techniques.Heliyon · 2024Article
- Process mining to investigate the relationship between clinical antecedents and injury risk, severity and return to play in professional sports.BMJ open sport & exercise medicine · 2024Article
- Performance and healthcare analysis in elite sports teams using artificial intelligence: a scoping review.Frontiers in sports and active living · 2024Article
- Managing Lower Limb Muscle Reinjuries in Athletes: From Risk Factors to Return-to-Play Strategies.Journal of functional morphology and kinesiology · 2023Review
- Predicting Injury and Illness with Machine Learning in Elite Youth Soccer: A Comprehensive Monitoring Approach over 3 Months.Journal of sports science & medicine · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This narrative review paper aimed to discuss the literature on machine learning applications in soccer with an emphasis on injury risk assessment. A secondary aim was to provide practical tips for the health and performance staff in soccer clubs on how machine learning can provide a competitive advantage. Performance analysis is the area with the majority of research so far. Other domains of soccer science and medicine with machine learning use are injury risk assessment, players' workload and wellness monitoring, movement analysis, players' career trajectory, club performance, and match attendance. Regarding injuries, which is a hot topic, machine learning does not seem to have a high predictive ability at the moment (models specificity ranged from 74.2%-97.7%. sensitivity from 15.2%-55.6% with area under the curve of 0.66-0.83). It seems, though, that machine learning can help to identify the early signs of elevated risk for a musculoskeletal injury. Future research should account for musculoskeletal injuries' dynamic nature for machine learning to provide more meaningful results for practitioners in soccer.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.